DOI QR코드

DOI QR Code

Analysis of the relationship between the end weight trait and the gene ADGRL2 in purebred landrace pigs using a Genome-wide association study

  • Kang, Ho-Chan (Division of Applied Life Science (BK21 plus), Gyeongsang National University) ;
  • Kim, Hee-Sung (Division of Applied Life Science (BK21 plus), Gyeongsang National University) ;
  • Lee, Jae-Bong (Korea Zoonosis Research Institute (KoZRI), Chonbuk National University) ;
  • Yoo, Chae-Kung (Institute of Agriculture and Life Science, Gyeongsang National University) ;
  • Choi, Tae-Jeong (Swine Science Division, National Institute of Animal Science, RDA) ;
  • Lim, Hyun-Tae (Division of Applied Life Science (BK21 plus), Gyeongsang National University)
  • 투고 : 2018.03.05
  • 심사 : 2018.05.08
  • 발행 : 2018.06.30

초록

The overall consumption of meat is increasing as the level of national income increases. The end weight is a trait closely associated with dressed meat. Genome-wide association study (GWAS) is an effective method of analyzing genetic variation and gene identification associated with a number of natural alternative traits because it can detect variations. So this paper did a GWAS analysis to identity the location on the genome related to the end weight in purebred landrace pigs and to explore the relevant candidate gene. This study identified a significant single nucleotide poly morphism (SNP) marker in chromosome 6 (ASGA0029422, $p=1.22{\times}10^{-6}$). Adhesion G protein-coupled receptor L2 (ADGRL2) was found to be the candidate gene at the identified SNP marker location. ADGRL2 genes have been found to be associated with cell development in relation to the external and internal environment of a cell. In addition, genotype and statistical analyses were done on nine variations on the exon of ADGRL2. The results show that the SNP marker (ASGA0029422, $p=1.32{\times}10^{-6}$) was significant, but the significance of the nine variations on the ADGRL2 exon was not verified. However, by performing further experiments and functional studies on other SNPs showing possible genetic ADGRL-Exon mutations, objects with high associations of high-end weights can be selected.

키워드

참고문헌

  1. Barrett JC, Fry B, Maller J, Daly MJ. 2005. Haploview: Analysis and visualization of LD and haplotype maps. Bioinformatics 21:263-265. https://doi.org/10.1093/bioinformatics/bth457
  2. Birren B, Green ED, Klapholz S, Myers RM, Roskams J. 1997. Genome analysis: A laboratory manual. p. 14. Cold Spring Harbor Laboratory Press, NY, USA.
  3. Borowska A, Henry R, Klaus W, Patrick FV, Tomasz S. 2017. Detection of pig genome regions determining production traits using an information theory approach. Livestock Science 205:31-35. https://doi.org/10.1016/j.livsci.2017.09.012
  4. Bruininx EM, van der Peet-Schwering CM, Schrama JW, Vereijken PF, Vesseur PC, Everts H, den Hartog LA , Beynen AC. 2001. Individually measured feed intake characteristics and growth performance of group-housed weanling pigs: Effects of sex, initial body weight, and body weight distribution within groups. Journal of Animal Science 79:301-308. https://doi.org/10.2527/2001.792301x
  5. Carney EE, Tran H, Bundy JW, Moreno R, Miller PS, Burky TE. 2009. Effect of dam parity on growth performance and immunity of weaned pigs. Nebraska Swine Reports 233:29-32.
  6. Cho CI, Lee JH, Park BH and Lee DH. 2013. A whole genome-wide association study for growth traits in a F2 crossbred population between landrace and Jeju indigenous pig. Journal of Agriculture & Life Science 47:75-84. [in Korean]
  7. Rosenbaum DM, Rasmussen SG, Kobilka BK. 2009. The structure and function of G-protein-coupled receptors. Nature 459:356-363. https://doi.org/10.1038/nature08144
  8. Dekkers JC. 2004. Commercial application of marker- and gene-assisted selection in livestock: Strategies and lessons. Journal of Animal Science 82 E-Suppl:E313-328.
  9. Do DN, Strathe AB, Jensen J, Mark T, Kadarmideen HN. 2013. Genetic parameters for different measures of feed efficiency and related traits in boars of three pig breeds. Journal of Animal Science 91:4069-79. https://doi.org/10.2527/jas.2012-6197
  10. Fan B, Onteru SK, Du ZQ, Garrick DJ, Stalder KJ, Rothschild MF. 2011. Genome-wide association study identifies loci for body composition and structural soundness traits in pigs. PLoS ONE 6:e14726. https://doi.org/10.1371/journal.pone.0014726
  11. Fix JS, Cassady JP, Holl JW, Herring WO, Culbertson MS, See MT. 2010. Effect of birth weight on survival and quality of commercial market swine. Livestock Science 132:98-106. https://doi.org/10.1016/j.livsci.2010.05.007
  12. Friend DW, Cunningham HM. 1996. Piglet birthweights and the order of farrowing. Canadian Journal of Comparative Medicine and Veterinary Science 30:179-182.
  13. Goddard ME, Hayes BJ. 2009. Mapping genes for complex traits in domestic animals and their use in breeding programmes. Nature Reviews Genetics 10:381-391. https://doi.org/10.1038/nrg2575
  14. Gu X, Feng C, Ma L, Song C, Wang Y, Da Y, Li H, Chen K, Ye S, Ge C, Hu X, Li N. 2011. Genome-wide association study of body weight in chicken F2 resource population. PLoS ONE 6:e21872. https://doi.org/10.1371/journal.pone.0021872
  15. Hamann J, Aust G, Arac D, Engel FB, Formstone C, Fredriksson R, Hall RA, Harty BL, Kirchhoff C, Knapp B, Krishnan A, Liebscher I, Lin HH, Martinelli DC, Monk KR, Peeters MC, Piao X, Promel S, Schoneberg T, Schwartz TW, Singer K, Stacey M, Ushkaryov YA, Vallon M, Wolfrum U, Wright MW, Xu L, Langenhan T, Schioth HB. 2015. International union of basic and clinical pharmacology. XCIV. Adhesion G protein-coupled receptors. Pharmacologicla Reviews 67:338-367.
  16. Han SH, Shin KY, Lee SS, Ko MS, Jeong DK, Jeon JT and Cho IC. 2008. Effects of ADCYP1R1, FABP3, FABP4, MC4R, MYL2 genotypes on growth traits in F2 population between landrace and Jeju native black pig. Journal of Animal Science and Technology 50:621-632. https://doi.org/10.5187/JAST.2008.50.5.621
  17. Horodyska J, Hamill RM, Varley PF, Reyer H, Wimmers K. 2017. Genome-wide association analysis and functional annotation of positional candidate genes for feed conversion efficiency and growth rate in pigs. PLoS One 12:e0173482. https://doi.org/10.1371/journal.pone.0173482
  18. Jung EJ, Park HB, Lee JB, Yoo CK, Kim BM, Kim HI, Kim BW, Lim HT. 2014. Genome-wide association analysis identifies quantitative trait loci for growth in a landrace purebred population. Animal Genetics 45:442-444. https://doi.org/10.1111/age.12117
  19. Kim Y, Ryu J, Woo J, Kim JB, Kim CY, Lee C. 2011. Genomewide association study reveals five nucleotide sequence variants for carcass traits in beef cattle. Animal Genetics 42:361-365. https://doi.org/10.1111/j.1365-2052.2010.02156.x
  20. Kim YS. 2009. Analysis of relationship between backfat thickness and major economic in swine. Master dissertation, Chonnam National University, Gwangju, Korea. [in Korean]
  21. Kolbehdari D, Wang Z, Grant JR, Murdoch B, Prasad A, Xiu Z, Marques E, Stothard P, Moore SS. 2009. A whole genome scan to map QTL for milk production traits and somatic cell score in Canadian holstein bulls. Journal of Animal Breeding and Genetics 126:216-227. https://doi.org/10.1111/j.1439-0388.2008.00793.x
  22. Lee DH, Do CH. 2012. Estimation of genetic parameters from longitudinal records of body weight of berkshire pigs. Asian-Australasian Journal of Animal Sciences 25:764-771. https://doi.org/10.5713/ajas.2011.11490
  23. Mahan DC, Lepine AJ. 1991. Effect of pig weaning weight and associated nursery feeding programs on subsequent performance to 105 kilograms body weight. Journal of Animal Science 69:1370-1378. https://doi.org/10.2527/1991.6941370x
  24. Main RG, Dritz SS, Tokach MD, Goodband RD, Nelssen JL. 2004. Increasing weaning age improve pig performance in a multisite production system. Journal of Animal Science 82:1499-1507. https://doi.org/10.2527/2004.8251499x
  25. Motsi P, Sakuhuni C, Halimani TE, Bhebhe E, Ndiweni PNB, Chimonyo M. 2006. Influence of parity, birth order, litter size and birth weight on duration of farrowing and birth intervals in commercial exotic sows in Zimbabwe. Animal Science Journal 82:569-574.
  26. Park CJ, Kang SS and Park YI. 1993. Effect of the difference in the initial weight on the results of performance testing in swine. Journal of Agricultural Science-Seoul University (Korea Repulic) 18:1-5. [in Korean]
  27. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, Maller J, Sklar P, de Bakker PI, Daly MJ, Sham PC. 2007. PLINK: A tool set for whole-genome association and population-based linkage analyses. The American Journal of Human Genetics 81:559-575. https://doi.org/10.1086/519795
  28. Reyer H, Varley PF, Murani E, Ponsuksili S, Wimmers K. 2017. Genetics of body fat mass and related traits in a pig population selected for leanness. Scientific Reports 7:9118. https://doi.org/10.1038/s41598-017-08961-4
  29. Rosendo A, Canario L, Druet T, Gogue J, Bidanel JP. 2007. Correlated responses of pre- and postweaning growth and backfat thickness to six generations of selection for ovulation rate or prenatal survival in French Large White pigs. Journal of Animal Science 85:3209-3217. https://doi.org/10.2527/jas.2007-0106
  30. Ryan TA, Joiner BL. 1976. Normal probability plots and tests for normality. Minitab, State College, Pennsylvania, USA.
  31. Sahana G, Kadlecova V, Hornshoj H, Nielsen B, Christensen OF. 2013. A genome-wide association scan in pig identifies novel regions associated with feed efficiency trait. Journal of Animal Science 91:1041-1050. https://doi.org/10.2527/jas.2012-5643
  32. Solanes FX, Grandinson K, Rydhmer L, Stern S, Andersson K, Lundeheim N. 2004. Direct and maternal influences on the early growth, fattening performance, and carcass traits of pigs. Livestock Production Science 88:199-212. https://doi.org/10.1016/j.livprodsci.2003.12.002
  33. Tomiyama M, Oikawa T, Hoque MA, Kanetani T, Mori H. 2009. Influence of early postweaning traits on genetic improvement of meat productivity in purebred Berkshire pigs. Journal of Animal Science 87:1613-1619. https://doi.org/10.2527/jas.2008-1214
  34. Wong GK, Liu B, Wang J, Zhang Y, Yang X, Zhang Z, Meng Q, Zhou J, Li D, Zhang J, Ni P, Li S, Ran L, Li H, Zhang J, Li R, Li S, Zheng H, Lin W, Li G, Wang X, Zhao W, Li J, Ye C, Dai M, Ruan J, Zhou Y, Li Y, He X, Zhang Y, Wang J, Huang X, Tong W, Chen J, Ye J, Chen C, Wei N, Li G, Dong L, Lan F, Sun Y, Zhang Z, Yang Z, Yu Y, Huang Y, He D, Xi Y, Wei D, Qi Q, Li W, Shi J, Wang M, Xie F, Wang J, Zhang X, Wang P, Zhao Y, Li N, Yang N, Dong W, Hu S, Zeng C, Zheng W, Hao B, Hillier LW, Yang SP, Warren WC, Wilson RK, Brandström M, Ellegren H, Crooijmans RP, van der Poel JJ, Bovenhuis H, Groenen MA, Ovcharenko I, Gordon L, Stubbs L, Lucas S, Glavina T, Aerts A, Kaiser P, Rothwell L, Young JR, Rogers S, Walker BA, van Hateren A, Kaufman J, Bumstead N, Lamont SJ, Zhou H, Hocking PM, Morrice D, de Koning DJ, Law A, Bartley N, Burt DW, Hunt H, Cheng HH, Gunnarsson U, Wahlberg P, Andersson L, Kindlund E, Tammi MT, Andersson B, Webber C, Ponting CP, Overton IM, Boardman PE, Tang H, Hubbard SJ, Wilson SA, Yu J, Wang J, Yang H. 2004. International chicken polymorphism map consortium. A genetic variation map for chicken with 2.8 million single-nucleotide polymorphisms. Nature 9:432(7018):717-722. https://doi.org/10.1038/nature03156
  35. Yang J, Lee SH, Goddard ME, Visscher PM. 2011. GCTA: A tool for genome-wide complex trait analysis. The American Journal of Human Genetics 88:76-82. https://doi.org/10.1016/j.ajhg.2010.11.011
  36. Yano K, Yamamoto E, Aya K, Takeuchi H, Lo PC, Hu L, Yamasaki M, Yoshida S, Kitano H, Hirano K, Matsuoka M. 2016. Genome-wide association study using whole-genome sequencing rapidly identifies new genes influencing agronomic traits in rice. Nature Genetics 48:927-934. https://doi.org/10.1038/ng.3596

피인용 문헌

  1. Single-Step Genome Wide Association Study Identifies QTL Signals for Untrimmed and Trimmed Thigh Weight in Italian Crossbred Pigs for Dry-Cured Ham Production vol.11, pp.6, 2018, https://doi.org/10.3390/ani11061612